Create summaries of text documents based on unsupervised extraction of most relevant sentences.

• extractive_simple.py
  Get most relevant sentences with tf-idf metrics
• extractive_text_rank.py
  TextRank implementation (based on word vectors)
• extractive_lex_rank.py
  LexRank implementation (cosine similarity on tf-idf metrics)

The directories in /data:

• source_texts:
  Excerpts of wikipedia biographies falling in 3 broad topics:
  • Tudor dynasty (marked with "a")
  • Midcentury Architects / Designer (marked with "b")
  • Stars of the silent movie area (marked with "c")
• target_texts:
  Very short texts based on source texts whith varying similarity, marked accordingly to the source texts. Also, one text about a movie star not included in source texts and one text about "Charlie Brown" without any topic affiliation (marked with "d").

This data is corresponding to: https://github.com/zushicat/text-topics

Download pre-trained word vectors glove.6B.zip, unzip file and place glove.6B.100d.txt in /data directory:
https://nlp.stanford.edu/projects/glove/

• "Wikipedia: Automatic summarization": https://en.wikipedia.org/wiki/Automatic_summarization
• "A Quick Introduction to Text Summarization in Machine Learning": https://towardsdatascience.com/a-quick-introduction-to-text-summarization-in-machine-learning-3d27ccf18a9f
• "An Overview of Summarization": https://blog.agolo.com/an-overview-of-summarization-551499a144d5
• "Text Summarization in Python: Extractive vs. Abstractive techniques revisited": https://rare-technologies.com/text-summarization-in-python-extractive-vs-abstractive-techniques-revisited/

• Graphs / Networks
  • "networkx": http://networkx.github.io/

• Gensim Summarize
  • "Tutorial: automatic summarization using Gensim": https://rare-technologies.com/text-summarization-with-gensim/
• TextRank
  • "An Introduction to Text Summarization using the TextRank Algorithm (with Python implementation)": https://www.analyticsvidhya.com/blog/2018/11/introduction-text-summarization-textrank-python/
• LexRank
  • "LexRank method for Text Summarization": https://iq.opengenus.org/lexrank-text-summarization/
  • "LexRank: Graph-based Lexical Centrality as Salience in Text Summarization": https://www.aaai.org/Papers/JAIR/Vol22/JAIR-2214.pdf